Multisite Recordings Research Articles

Opposite effects of ketamine and deep brain stimulation on rat thalamocortical information processing

Sensory and cognitive deficits are common in schizophrenia. They are associated with abnormal brain rhythms, including disturbances in γ frequency (30-80 Hz) oscillations (GFO) in cortex-related networks. However, the underlying anatomofunctional mechanisms remain elusive. Clinical and experimental evidence suggests that these deficits result from a hyporegulation of glutamate N-methyl-D-aspartate receptors. Here we modeled these deficits in rats with ketamine, a non-competitive N-methyl-D-aspartate receptor antagonist and a translational psychotomimetic substance at subanesthetic doses. We tested the hypothesis that ketamine-induced sensory deficits involve an impairment of the ability of the thalamocortical (TC) system to discriminate the relevant information from the baseline activity. Furthermore, we wanted to assess whether ketamine disrupts synaptic plasticity in TC systems. We conducted multisite network recordings in the rat somatosensory TC system, natural stimulation of the vibrissae and high-frequency electrical stimulation (HFS) of the thalamus. A single systemic injection of ketamine increased the amount of baseline GFO, reduced the amplitude of the sensory-evoked TC response and decreased the power of the sensory-evoked GFO. Furthermore, cortical application of ketamine elicited local and distant increases in baseline GFO. The ketamine effects were transient. Unexpectedly, HFS of the TC pathway had opposite actions. In conclusion, ketamine and thalamic HFS have opposite effects on the ability of the somatosensory TC system to discriminate the sensory-evoked response from the baseline GFO during information processing. Investigating the link between the state and function of the TC system may conceptually be a key strategy to design innovative therapies against neuropsychiatric disorders.

A13 Phenotyping neural networks in an ovine model of huntington's disease

A large animal transgenic model of Huntington9s disease (HD) has been recently developed in domestic sheep (Ovis aries L). 1 Sheep are a long-lived species with large brains, complex basal ganglia and convoluted neocortex; compared to standard models in short-lived rodents with lissencephalic cortices, this ovine model may therefore be better-suited for electrophysiological characterisations of early disease stages and for the development of novel treatments. Using a sheep model will also reduce costs relative to non-human primates, and enables large-scale, long-term and multi-site electrophysiological recording during behavioural testing paradigms. 2 Sleep is an essential and ubiquitous brain state that is known to deteriorate in humans suffering from HD. As a first step towards assessing the normal electrophysiological features of sheep, we aimed to characterise sleep architecture using electroencephalography in healthy sheep. In addition we performed some common behavioural manipulations known to modulate sleep architecture. These include sleep deprivation and learning prior to sleep. The method can be expanded to generate sensitive biomarkers of intra-cortical network activity and interactions between brain structures in the behaving animal. If deterioration of these network interactions precedes the appearance of overt symptoms, this could then be targeted for treatments that might delay symptom onset. We also present deep brain recordings (of local field potentials and single neuron spike activity) from an anaesthetised animal as a proof of concept. Sheep disease models offer unique opportunities for long term in vivo electrophysiological testing, with the potential lead to novel therapeutic treatments targeting early stages of HD progression.

Use of multi-electrode array recordings in studies of network synaptic plasticity in both time and space

Simultaneous multisite recording using multi-electrode arrays (MEAs) in cultured and acutely-dissociated brain slices and other tissues is an emerging technique in the field of network electrophysiology. Over the past 40 years, great efforts have been made by both scientists and commercial concerns, to advance this technique. The MEA technique has been widely applied to many regions of the brain, retina, heart and smooth muscle in various studies at the network level. The present review starts from the development of MEA techniques and their uses in brain preparations, and then specifically concentrates on the use of MEA recordings in studies of synaptic plasticity at the network level in both the temporal and spatial domains. Because the MEA technique helps bridge the gap between single-cell recordings and behavioral assays, its wide application will undoubtedly shed light on the mechanisms underlying brain functions and dysfunctions at the network level that remained largely unknown due to the technical difficulties before it matured.

Fabrication of hollow SiO2 nanoneedle array and characterization of simultaneous multi-site ion-conductance recordings for cell morphology imaging

To realize high-speed and high-resolution imaging of the morphology of living cells in a solution, our group has been developing a technique called simultaneous multi-site ion-conductance microscopy. In this study, hollow nanoneedles in an array were successfully fabricated in our batch fabrication process for multi-site ion-conductance recording. In addition, the characterization of the ion conductance with a glass pipette using an AC-modulated input voltage revealed that morphology imaging of a HeLa cell was possible and a SPICE model was applicable to the estimation of the ion-conductance change. Moreover, this technique was found to be applicable to simultaneous multi-site ion-conductance microscopy with an AC-modulated input voltage at a frequency of less than 100 Hz.

Outside looking in: nanotube transistor intracellular sensors.

Nanowire-based field-effect transistors, including devices with planar and three-dimensional configurations, are being actively explored as detectors for extra- and intracellular recording due to their small size and high sensitivities. Here we report the synthesis, fabrication, and characterization of a new needle-shaped nanoprobe based on an active silicon nanotube transistor, ANTT, that enables high-resolution intracellular recording. In the ANTT probe, the source/drain contacts to the silicon nanotube are fabricated on one end, passivated from external solution, and then time-dependent changes in potential can be recorded from the opposite nanotube end via the solution filling the tube. Measurements of conductance versus water-gate potential in aqueous solution show that the ANTT probe is selectively gated by potential changes within the nanotube, thus demonstrating the basic operating principle of the ANTT device. Studies interfacing the ANTT probe with spontaneously beating cardiomyocytes yielded stable intracellular action potentials similar to those reported by other electrophysiological techniques. In addition, the straightforward fabrication of ANTT devices was exploited to prepare multiple ANTT structures at the end of single probes, which enabled multiplexed recording of intracellular action potentials from single cells and multiplexed arrays of single ANTT device probes. These studies open up unique opportunities for multisite recordings from individual cells through cellular networks.

A novel environmental chamber for neuronal network multisite recordings

Environmental stability is a critical issue for neuronal networks in vitro. Hence, the ability to control the physical and chemical environment of cell cultures during electrophysiological measurements is an important requirement in the experimental design. In this work, we describe the development and the experimental verification of a closed chamber for multisite electrophysiology and optical monitoring. The chamber provides stable temperature, pH and humidity and guarantees cell viability comparable to standard incubators. Besides, it integrates the electronics for long-term neuronal activity recording. The system is portable and adaptable for multiple network housings, which allows performing parallel experiments in the same environment. Our results show that this device can be a solution for long-term electrophysiology, for dual network experiments and for coupled optical and electrical measurements.

SigMate: A Matlab-based automated tool for extracellular neuronal signal processing and analysis

Rapid advances in neuronal probe technology for multisite recording of brain activity have posed a significant challenge to neuroscientists for processing and analyzing the recorded signals. To be able to infer meaningful conclusions quickly and accurately from large datasets, automated and sophisticated signal processing and analysis tools are required. This paper presents a Matlab-based novel tool, “SigMate”, incorporating standard methods to analyze spikes and EEG signals, and in-house solutions for local field potentials (LFPs) analysis. Available modules at present are – 1. In-house developed algorithms for: data display (2D and 3D), file operations (file splitting, file concatenation, and file column rearranging), baseline correction, slow stimulus artifact removal, noise characterization and signal quality assessment, current source density (CSD) analysis, latency estimation from LFPs and CSDs, determination of cortical layer activation order using LFPs and CSDs, and single LFP clustering; 2. Existing modules: spike detection, sorting and spike train analysis, and EEG signal analysis. SigMate has the flexibility of analyzing multichannel signals as well as signals from multiple recording sources. The in-house developed tools for LFP analysis have been extensively tested with signals recorded using standard extracellular recording electrode, and planar and implantable multi transistor array (MTA) based neural probes. SigMate will be disseminated shortly to the neuroscience community under the open-source GNU-General Public License.

Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function

Neural chips, which are capable of simultaneous multisite neural recording and stimulation, have been used to detect and modulate neural activity for almost thirty years. As neural interfaces, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information of neuroplasticity. This novel nano-neuron interface may potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single-cell level and even inside the cell. From the Clinical EditorThe authors demonstrate the utility of a neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes. The new device can be used to stimulate and/or monitor signals from brain tissue in vitro and for monitoring dynamic information of neuroplasticity both intracellularly and at the single cell level including neuroelectrical and neurochemical activities.

Initiation and Propagation of Action Potentials in Gonadotropin-Releasing Hormone Neuron Dendrites

Gonadotropin-releasing hormone (GnRH) neurons are the final output neurons in a complex neuronal network that regulates fertility. The morphology of GnRH neuron dendrites is very different to other central neurons in that they are very long, thin, and unbranched. To study the function of these dendrites, we have used Na(+) and Ca(2+) imaging in combination with dual soma and dendrite electrical recordings in brain slices from GnRH-GFP mice. Here, we show that GnRH neurons actively propagate Na(+) spikes throughout their dendrites. Multisite dendritic recordings confirmed that these spikes were observed in one of the dendrites before the soma in the great majority of neurons tested. Na(+) imaging experiments revealed that the initial 150 μm of dendrite has a higher density of functional Na(+) channels than more distal regions, suggesting that this region of dendrite is highly excitable and may be the site of spike initiation. Finally, we show that the depolarization from dendritic spikes opens voltage-gated Ca(2+) channels giving rise to dendritic Ca(2+) transients. Together, these findings suggest that the proximal dendrites of GnRH neurons are highly excitable and are likely to be the site of action potential initiation in these neurons.

G220014 細胞形態イメージングのための多点同時計測イオンコンダクタンス顕微鏡の開発

Scanning ion conductance microscopy (SICM) is a useful tool for imaging of cell morphology in a solution. To further understand cell functions, it is necessary to obtain images of multiple cells. Therefore, we have been developing simultaneous multi-site ion conductance microscope for morphology imaging of multiple cells. This paper reported characterization of multi-site ion conductance recordings by using a modulation method with probe vibration. Furthermore, fabrication of a hollow SiO_2 nanoneedle array using electron beam (EB) lithography, DR1E and standard microfabrication techniques was executed.

Deep Brain Stimulation for Movement Disorders – A History of Success and Challenges to Conquer

Deep Brain Stimulation for Movement Disorders – A History of Success and Challenges to Conquer

A novel symbolization scheme for multichannel recordings with emphasis on phase information and its application to differentiate EEG activity from different mental tasks

Symbolic dynamics is a powerful tool for studying complex dynamical systems. So far many techniques of this kind have been proposed as a means to analyze brain dynamics, but most of them are restricted to single-sensor measurements. Analyzing the dynamics in a channel-wise fashion is an invalid approach for multisite encephalographic recordings, since it ignores any pattern of coordinated activity that might emerge from the coherent activation of distinct brain areas. We suggest, here, the use of neural-gas algorithm (Martinez et al. in IEEE Trans Neural Netw 4:558-569, 1993) for encoding brain activity spatiotemporal dynamics in the form of a symbolic timeseries. A codebook of k prototypes, best representing the instantaneous multichannel data, is first designed. Each pattern of activity is then assigned to the most similar code vector. The symbolic timeseries derived in this way is mapped to a network, the topology of which encapsulates the most important phase transitions of the underlying dynamical system. Finally, global efficiency is used to characterize the obtained topology. We demonstrate the approach by applying it to EEG-data recorded from subjects while performing mental calculations. By working in a contrastive-fashion, and focusing in the phase aspects of the signals, we show that the underlying dynamics differ significantly in their symbolic representations. The online version of this article (doi:10.1007/s11571-011-9186-5) contains supplementary material, which is available to authorized users.

Classifying heterogeneity of spontaneous up-states: A method for revealing variations in firing probability, engaged neurons and Fano factor

The dynamics of spontaneous and sensory-evoked up-states have been recently compared, in multi-site recordings in vivo and found to have similarities and differences. Also in vitro, this is evident because we here describe a novel computational method to classify into statistically different states the spontaneous reverberating activity recorded from long-term (12–18 days- in vitro) cultured cortical neurons (from 60-site multi- electrode arrays, MEA). State classification was performed by spike number time histograms (SNTH, or other burst features) of excitatory and inhibitory neuron clusters and revealed that in novel identified states the number of engaged neurons or up-state duration can change. To improve the characterization of each state we also computed the firing spike histograms (FSH) which revealed a new facet of the firing probability of clusters. In exemplary functional experiments we show that: (i) up to 6–7 states can be safely categorized during several hours of recordings without observing spike rate changes, (ii) they disappear after a short pharmacological stimulation being replaced with novel states active and living up to 6–8 h, (iii) antagonists in the nM range can split the activity of a homogeneous network into the chronological coexistence of 2 states, one completely different and one not significantly different from control state. In conclusion, we believe that this novel procedure better characterizes the number of functional states of a network and opens up the possibility of predicting the elementary “vocabulary” used by small networks of neurons.

Webinar Training: an acceptable, feasible and effective approach for multi-site medical record abstraction: the BOWII experience

Backgroundor training is a key element in creating valid and reliable data collection procedures. The choice between in-person vs. remote or simultaneous vs. sequential abstractor training has considerable consequences for time and resource utilization. We conducted a web-based (webinar) abstractor training session to standardize training across six individual Cancer Research Network (CRN) sites for a study of breast cancer treatment effects in older women (BOWII). The goals of this manuscript are to describe the training session, its participants and participants' evaluation of webinar technology for abstraction training.FindingsA webinar was held for all six sites with the primary purpose of simultaneously training staff and ensuring consistent abstraction across sites. The training session involved sequential review of over 600 data elements outlined in the coding manual in conjunction with the display of data entry fields in the study's electronic data collection system. Post-training evaluation was conducted via Survey Monkey©. Inter-rater reliability measures for abstractors within each site were conducted three months after the commencement of data collection.Ten of the 16 people who participated in the training completed the online survey. Almost all (90%) of the 10 trainees had previous medical record abstraction experience and nearly two-thirds reported over 10 years of experience. Half of the respondents had previously participated in a webinar, among which three had participated in a webinar for training purposes. All rated the knowledge and information delivered through the webinar as useful and reported it adequately prepared them for data collection. Moreover, all participants would recommend this platform for multi-site abstraction training. Consistent with participant-reported training effectiveness, results of data collection inter-rater agreement within sites ranged from 89 to 98%, with a weighted average of 95% agreement across sites.ConclusionsConducting training via web-based technology was an acceptable and effective approach to standardizing medical record review across multiple sites for this group of experienced abstractors. Given the substantial time and cost savings achieved with the webinar, coupled with participants' positive evaluation of the training session, researchers should consider this instructional method as part of training efforts to ensure high quality data collection in multi-site studies.

Auditory Influences in V1 of Mice Induced by Varying Anesthesia Level

Anesthesia affects cortical response properties and induces changes in functional network connectivity. Many studies in sensory neurophysiology do not explicitly differentiate between anesthetic states and possibly underestimate the effect of anesthetic level on cortical response properties. To investigate this question, we performed simultaneous multisite recordings in V1 of C57bl/6 mice under continuously changing inspiratory isoflurane concentration from low to high dosage. During the continuous change of anesthesia level we presented visual and auditory stimuli. At all levels of anesthesia, visual stimulation evoked responses in V1. However, during light anesthesia auditory stimulation slightly suppressed ongoing LFP activity in V1. With increasing anesthesia levels this suppression vanished, and at a specific point a discrete change in sensory responsiveness of V1 to auditory stimulation appeared. At this discrete point auditory suppression was reversed into auditory induced activation of V1. This transition in properties was coincident with the appearance of burst-suppression. The responses during burst suppression state had long latency and resembled spontaneous bursts. This presumably unspecific auditory effect in V1 disappeared as soon as isoflurane concentration level dropped below a certain level. The results demonstrate that in the extreme case heteromodal effects can be induced by varying anesthesia level.

Inhibition recruitment in prefrontal cortex during sleep spindles and gating of hippocampal inputs

During light slow-wave sleep, the thalamo-cortical network oscillates in waxing-and-waning patterns at about 7 to 14 Hz and lasting for 500 ms to 3 s, called spindles, with the thalamus rhythmically sending strong excitatory volleys to the cortex. Concurrently, the hippocampal activity is characterized by transient and strong excitatory events, Sharp-Waves-Ripples (SPWRs), directly affecting neocortical activity--in particular the medial prefrontal cortex (mPFC)--which receives monosynaptic fibers from the ventral hippocampus and subiculum. Both spindles and SPWRs have been shown to be strongly involved in memory consolidation. However, the dynamics of the cortical network during natural sleep spindles and how prefrontal circuits simultaneously process hippocampal and thalamo-cortical activity remain largely undetermined. Using multisite neuronal recordings in rat mPFC, we show that during sleep spindles, oscillatory responses of cortical cells are different for different cell types and cortical layers. Superficial neurons are more phase-locked and tonically recruited during spindle episodes. Moreover, in a given layer, interneurons were always more modulated than pyramidal cells, both in firing rate and phase, suggesting that the dynamics are dominated by inhibition. In the deep layers, where most of the hippocampal fibers make contacts, pyramidal cells respond phasically to SPWRs, but not during spindles. Similar observations were obtained when analyzing γ-oscillation modulation in the mPFC. These results demonstrate that during sleep spindles, the cortex is functionnaly "deafferented" from its hippocampal inputs, based on processes of cortical origin, and presumably mediated by the strong recruitment of inhibitory interneurons. The interplay between hippocampal and thalamic inputs may underlie a global mechanism involved in the consolidation of recently formed memory traces.

Spatially arranged microelectrode probes for multi-site electroretinogram recordings in the isolated mouse retina

Spatially arranged microelectrode probes for multi-site electroretinogram recordings in the isolated mouse retina

A bi-directional neuro-robotic system to study computational properties of cell assemblies

Behaviors, from simple to most complex, require a two-way interaction with the environment and the contribution of different brain areas depending on the orchestrated activation of neuronal assemblies. Understanding how information is coded and how synaptic mechanisms are implemented in physiological as well as pathological networks is one of the major challenges of neuroscience. Researchers have begun to study the mechanisms of adaptive behaviors interfacing biological models of the brain with robots by means of electrophysiological techniques [1]. Among the others, dissociated cultures coupled to MEAs (i.e. Micro Electrode Arrays) provide a suitable experimental substrate for embodied electrophysiology since they allow long-term multisite recording and stimulation [2,3]. Here we will present what the main components of an experimental system are, in order to support the execution of neuro-robotic experiments. To establish a bidirectional communication between the neuronal preparation (network module) and a mobile robot (robotic module), the electrophysiological signals need to be translated into motor commands for the robot (decoding of neural activity), and at the same time the sensory signal from the robot need to be translated into a pattern of electrical stimulation (coding of sensory information). Both modules can be either real or simulated. More specifically: (i) the network module can be a culture of dissociated cortical neurons coupled to a commercial Micro Electrode Array (MCS, Reutlingen, Germany) or a simulation of that obtained by our simulator NeuVision, which allows to simulate large scale neuronal networks [4]; (ii) the robot can be the commercial mobile robot Khepera, manufactured by K-Team (Yverdon-les-bains, Switzerland) or its simulation, again obtained by NeuVision. We fully simulated a closed-loop experiment in which a robot, controlled by the electrical activity of a neural network, moves in a circular arena containing some obstacles. To characterize the propagation of either spontaneous or evoked network bursts (i.e. a pattern of activity which involve almost the entire neuronal network), we made use of the center of activity trajectory (CAT) [5]. We observed that CATs of evoked network bursts follow typical paths, while CATs of spontaneous network bursts are not regular. Moreover we fully simulated a closed-loop experiment where the CAT method was used to generate motor commands. The obtained control of the robot allowed to accomplish an obstacle avoidance task. Real modules have also been assembled and tested: preliminary experiments have been performed implementing a simple decoding strategy based on the mean firing rate of a culture region. Similarly, robot sensors provided information on obstacles distance which has been coded with a frequency-modulated electrical stimulation. In conclusion, we think that a synergistic approach taking advantage of both simulated and real components could be crucial to increase the effectiveness of electrophysiological experiments in order to understand how networks encode information. The modularity of the software architecture makes easy to interface within the same experiment either real or simulated components such as large-scale neural network and robots.

Synaptic dysfunction in hippocampus of transgenic mouse models of Alzheimer's disease: A multi-electrode array study

APP.V717I and Tau.P301L transgenic mice develop Alzheimer's disease pathology comprising important aspects of human disease including increased levels of amyloid peptides, cognitive and motor impairment, amyloid plaques and neurofibrillary tangles. The combined model, APP.V717I × Tau.P301L bigenic mice (biAT mice) exhibit aggravated amyloid and tau pathology with severe cognitive and behavioral defects. In the present study, we investigated early changes in synaptic function in the CA1 and CA3 regions of acute hippocampal slices of young APP.V717I, Tau.P301L and biAT transgenic animals. We have used planar multi-electrode arrays (MEA) and improved methods for simultaneous multi-site recordings from two hippocampal sub-regions. In the CA1 region, long-term potentiation (LTP) was severely impaired in all transgenic animals when compared with age-matched wild-type controls, while basal synaptic transmission and paired-pulse facilitation were minimally affected. In the CA3 region, LTP was normal in Tau.P301L and APP.V717I but clearly impaired in biAT mice. Surprisingly, frequency facilitation in CA3 was significantly enhanced in Tau.P301L mice, while not affected in APP.V717I mice and depressed in biAT mice. The findings demonstrate important synaptic changes that differ considerably in the hippocampal sub-regions already at young age, well before the typical amyloid or tau pathology is evident.

On the extension of ordinal time series analysis for multisite recordings: A new method and its use in discriminating EEG activity during different mental tasks

On the extension of ordinal time series analysis for multisite recordings: A new method and its use in discriminating EEG activity during different mental tasks